Posts Tagged ‘SPSS’

Organizations interested in using analytics to predict outcomes will score data pools by applying an appropriate predictive model. Pre-built predictive models are becoming increasingly available in the market place. Data scientists that are knowledge experts in particular areas are developing models that have increasingly better success rates. However the best approach may be for an […]

Defining what lift is “Lift” is the measure used to determine how well your targeting model does at prophesying cases as having a greater response with respect to the population as a whole. Your model may be doing its job if the response (within the target) is better than the average response of the population […]

IBM SPSS Statistics – Data Management Toolset (DMS) In a recent blog post I listed some of the more helpful “data management tools” offered within IBM SPSS Statistics version 20 (Case Summaries, Replace Missing Values, Transform and Compute, Recode, Select Cases, Sort Cases and Merge Files) and would like to review them today. These tools […]

Getting Started…Again Back to Statistics; I restart IBM SPSS and from the startup/open dialog, locate my previously defined data file from the “Open an existing data source” list and click OK. My file opens in the data editor (just as I left it) and the Statistics Viewer shows the very first transaction “GET” (and then […]

Last time I mentioned IBM SPSS collaboration and deployment services and promised to talk more about it – so here we go: Analytical Assets Organizations positioning themselves to take full advantage of analytics will look to separate the effort of developing analytical assets and actually using them – between “creators” and “consumers”.  Generally speaking, an […]

    The basic steps in data analysis might be simplified into (1) Identifying data, (2) Selecting an analysis and summarization method and (3) Presenting the results. Over the next couple of weeks I will look at using IBM SPSS version 20 to accomplish these tasks. Today, I want to focus on loading a data […]

If you work within the rapidly expanding analytics space, you will need to think about defining and sharing statistical models between applications. PMML (or Predictive Model Markup Language) is an XML-based language developed by the Data Mining Group (DMG) for this purpose. I’d like to pass on some of the essentials: The Basics PMML provides […]